adaa.simu.jack: An R function for AD model simulation

In qgtools: Generalized Quantitative Genetics Data Analyses

Description

An R function for AD model simulation with generated data set.

Usage

adaa.simu.jack(Y, Ped, method = NULL, JacNum = NULL, JacRep = NULL, ALPHA = NULL)

Arguments

Y	A matrix of simulated data set
Ped	A pedigree matrix including Environment, Female, Male, Generation, with or without block is required. So the matrix should include either 4 columns or 5 columns.
method	The default linear mixed model approach is MINQUE. Users can choose both or one of two linear mixed model approaches, REML and MINQUE.
JacNum	Number of jackknife groups. The default is 10.
JacRep	Repeating times for jackknife process. The default is 1.
ALPHA	A preset nominal probability level.The default is 0.05.

Value

Return list of simulated results for variance components.

Author(s)

Jixiang Wu <[e-mail]>

References

Rao, C.R. 1971. Estimation of variance and covariance components-MINQUE theory. J Multiva Ana 1:19

Rao, C. R. and Kleffe, J. 1980. Estimation of variance components. In Handbook of Statistics. Vol. l: 1-40. Krishnaiah, P. R. ed. New York. North-Holland.

Searle, S. R., Casella, G. and McCulloch, C. E. 1992. Variance Components. John Wiley & Sons, Inc. New York.

Wu J (2012) GenMod: An R package for various agricultural data analyses. ASA, CSSA, and SSSA 2012 International Annual Meetings, Cincinnati, OH, p 127

Wu J., Bondalapati K., Glover K., Berzonsky W., Jenkins J.N., McCarty J.C. 2013. Genetic analysis without replications: model evaluation and application in spring wheat. Euphytica. 190:447-458

Zhu J. 1989. Estimation of Genetic Variance Components in the General Mixed Model. Ph.D. Dissertation, NC State University, Raleigh, U.S.A

Examples

  library(qgtools)
  data(cotf2)
  dat=cotf2[which(cotf2$Env==1),]
  Ped=dat[,c(1:5)]
  Y=dat[,-c(1:5)]
  Y=data.frame(Y)
  #Ped=cotf2[,c(1:5)]
  #Y=cotf2[,-c(1:5)]
  YS=adaa.simudata(Y,Ped,v=rep(20,5),b=c(100),SimuNum=10)
  res=adaa.simu.jack(YS,Ped,JacNum=5)
  res
  ##End

qgtools documentation built on Dec. 19, 2019, 1:09 a.m.